Effects of Long-Range Correlations in DNA on Sequence Alignment Score Statistics

Messer, Philipp W.; Bundschuh, Ralf; Vingron, Martin; Arndt, Peter F.

doi:10.1089/cmb.2007.r008

Cited by 11 publications

(17 citation statements)

References 29 publications

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“…5 uppermost row, first three panels). The one dimensional correlation function C(r ) of these SNP based sequences is calculated using the procedure of Messer et al 48. (see Methods).…”

Section: Resultsmentioning

confidence: 99%

Complex multifractal nature in Mycobacterium tuberculosis genome

Mandal

Roychowdhury

Chirom

et al. 2017

Sci Rep

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The mutifractal and long range correlation (C(r)) properties of strings, such as nucleotide sequence can be a useful parameter for identification of underlying patterns and variations. In this study C(r) and multifractal singularity function f(α) have been used to study variations in the genomes of a pathogenic bacteria Mycobacterium tuberculosis. Genomic sequences of M. tuberculosis isolates displayed significant variations in C(r) and f(α) reflecting inherent differences in sequences among isolates. M. tuberculosis isolates can be categorised into different subgroups based on sensitivity to drugs, these are DS (drug sensitive isolates), MDR (multi-drug resistant isolates) and XDR (extremely drug resistant isolates). C(r) follows significantly different scaling rules in different subgroups of isolates, but all the isolates follow one parameter scaling law. The richness in complexity of each subgroup can be quantified by the measures of multifractal parameters displaying a pattern in which XDR isolates have highest value and lowest for drug sensitive isolates. Therefore C(r) and multifractal functions can be useful parameters for analysis of genomic sequences.

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“…5 uppermost row, first three panels). The one dimensional correlation function C(r ) of these SNP based sequences is calculated using the procedure of Messer et al 48. (see Methods).…”

Section: Resultsmentioning

confidence: 99%

Complex multifractal nature in Mycobacterium tuberculosis genome

Mandal

Roychowdhury

Chirom

et al. 2017

Sci Rep

View full text Add to dashboard Cite

show abstract

“…We consider random events because it is the simplest assumption and because it generates sequences with a reasonable degree of homogeneity [51], [52]. (It is known that genomes have long-range correlations that require tandem SDs to generate [46], [57]. Since tandem duplications do not effect , for simplicity they are not given special treatment in this study.)…”

Section: Discussionmentioning

confidence: 99%

Universal Global Imprints of Genome Growth and Evolution – Equivalent Length and Cumulative Mutation Density

et al. 2010

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BackgroundSegmental duplication is widely held to be an important mode of genome growth and evolution. Yet how this would affect the global structure of genomes has been little discussed.Methods/Principal FindingsHere, we show that equivalent length, or , a quantity determined by the variance of fluctuating part of the distribution of the -mer frequencies in a genome, characterizes the latter's global structure. We computed the s of 865 complete chromosomes and found that they have nearly universal but (-dependent) values. The differences among the of a chromosome and those of its coding and non-coding parts were found to be slight.ConclusionsWe verified that these non-trivial results are natural consequences of a genome growth model characterized by random segmental duplication and random point mutation, but not of any model whose dominant growth mechanism is not segmental duplication. Our study also indicates that genomes have a nearly universal cumulative “point” mutation density of about 0.73 mutations per site that is compatible with the relatively low mutation rates of (15)10/site/Mya previously determined by sequence comparison for the human and E. coli genomes.

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“…It has been proved that in the limit of infinitely long sequences, ungapped alignment scores for random Markov-dependent sequences are still distributed according to the EVD (Karlin and Dembo, 1992). Gapped alignments of correlated random sequences accounted for by a null model have been shown numerically to correspond to an EVD too (Messer et al, 2007). Notably, the values of the statistical parameters differed substantially from those obtained for iid sequences.…”

Section: Introductionmentioning

confidence: 96%

Estimating statistical significance of local protein profile-profile alignments

Margelevičius

2018

Preprint

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Alignment of sequence families described by profiles provides a sensitive means for establishing homology between proteins and is important in protein evolutionary, structural, and functional studies. In the context of a steadily growing amount of sequence data, estimating the statistical significance of alignments, including profile-profile alignments, plays a key role in alignment-based homology search algorithms. Still, it is an open question as to what and whether one type of distribution governs profile-profile alignment score, especially when profile-profile substitution scores involve such terms as secondary structure predictions. This study presents a methodology for estimating the statistical significance of this type of alignments. The methodology rests on a new algorithm developed for generating random profiles such that their alignment scores are distributed similarly to those obtained for real unrelated profiles. We show that improvements in statistical accuracy and sensitivity and high-quality alignment rate result from statistically characterizing alignments by establishing the dependence of statistical parameters on various measures associated with both individual and pairwise profile characteristics. Implemented in the COMER software, the proposed methodology yielded an increase of up to 34.2% in the number of true positives and up to 61.8% in the number of high-quality alignments with respect to the previous version of the COMER method. A new version (v1.5.1) of the COMER software is available at https://sourceforge.net/projects/comer. The COMER software is also available on Github at https://github.com/minmarg/comer and as a Docker image (https://hub.docker.com/r/minmar/comer).

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Effects of Long-Range Correlations in DNA on Sequence Alignment Score Statistics

Cited by 11 publications

References 29 publications

Complex multifractal nature in Mycobacterium tuberculosis genome

Complex multifractal nature in Mycobacterium tuberculosis genome

Universal Global Imprints of Genome Growth and Evolution – Equivalent Length and Cumulative Mutation Density

Estimating statistical significance of local protein profile-profile alignments

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